144 citations · 237 across the 9 of their papers we have counts for
5 papers · 1 filter
Do We Need Perfect Data? Leveraging Noise for Domain Generalized Segmentation
Taeyeong Kim, SeungJoon Lee, Jung Uk Kim +1
Domain generalization in semantic segmentation faces challenges from domain shifts, particularly under adverse conditions. While diffusion-based data generation methods show promis…
Multispectral Pedestrian Detection with Sparsely Annotated Label
Chan Lee, Seungho Shin, Gyeong-Moon Park +1
Although existing Sparsely Annotated Object Detection (SAOD) approches have made progress in handling sparsely annotated environments in multispectral domain, where only some pedes…
Towards Model-Agnostic Dataset Condensation by Heterogeneous Models
Jun-Yeong Moon, Jung Uk Kim, Gyeong-Moon Park
Abstract. The advancement of deep learning has coincided with the proliferation of both models and available data. The surge in dataset sizes and the subsequent surge in computatio…
Online Class Incremental Learning on Stochastic Blurry Task Boundary via Mask and Visual Prompt Tuning
Jun-Yeong Moon, Keon-Hee Park, Jung Uk Kim +1
Continual learning aims to learn a model from a continuous stream of data, but it mainly assumes a fixed number of data and tasks with clear task boundaries. However, in real-world…
Faster Segment Anything: Towards Lightweight SAM for Mobile Applications
Chaoning Zhang, Dongshen Han, Yu Qiao +4
Segment Anything Model (SAM) has attracted significant attention due to its impressive zero-shot transfer performance and high versatility for numerous vision applications (like im…